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Frequent drought and high temperature conditions in California vineyards necessitate plant stress detection to support irrigation management strategies and decision making. Remote sensing provides a powerful tool to continuously monitor vegetation function across spatial and temporal scales. In this study, we utilized a tower-based optical-remote sensing system to continuously monitor four vineyard subplots in California’s Central Valley. We compared the performance of the greenness-based normalized difference vegetation index (NDVI) and the physiology-based photochemical reflectance index (PRI) to track variations of eddy covariance estimated gross primary productivity (GPP) during four stress events between July and September 2020. Our results demonstrate that NDVI was invariant during stress events. In contrast, PRI was effective at tracking the short-term stress-induced declines and recovery of GPP associated with soil water depletion and increased air temperature, as well as reductions in GPP from decreased PAR caused by smokey conditions from nearby fires. Canopy-scale remote sensing can provide continuous real-time data, and physiology-based vegetation indices such as PRI can be used to monitor variation of photosynthetic activity during stress events to aid in management decisions.

Remote sensing methods enable detection of solar-induced chlorophyll a fluorescence. However, to unleash the full potential of this signal, intensive cross-disciplinary work is required to harmonize biophysical and ecophysiological studies. For decades, the dynamic nature of chlorophyll a fluorescence (ChlaF) has provided insight into the biophysics and ecophysiology of the light reactions of photosynthesis from the subcellular to leaf scales. Recent advances in remote sensing methods enable detection of ChlaF induced by sunlight across a range of larger scales, from using instruments mounted on towers above plant canopies to Earth-orbiting satellites. This signal is referred to as solar-induced fluorescence (SIF) and its application promises to overcome spatial constraints on studies of photosynthesis, opening new research directions and opportunities in ecology, ecophysiology, biogeochemistry, agriculture and forestry. However, to unleash the full potential of SIF, intensive cross-disciplinary work is required to harmonize these new advances with the rich history of biophysical and ecophysiological studies of ChlaF, fostering the development of next-generation plant physiological and Earth-system models. Here, we introduce the scale-dependent link between SIF and photosynthesis, with an emphasis on seven remaining scientific challenges, and present a roadmap to facilitate future collaborative research towards new applications of SIF.

The phenology of montane conifer forests is likely to shift in response to climate change and altered seasonal dynamics of light, temperature, and moisture. Solar-induced fluorescence (SIF) is expected to provide substantial improvement for mapping temporal changes in evergreen gross primary production (GPP) over greenness-based remote sensing indices. The utility of SIF to monitor seasonal changes in the phenology of conifer photosynthesis depends on the degree to which GPP and SIF respond in synchrony to key environmental drivers. However, to what extent SIF and GPP become decoupled by responding differently to the combined effects of light and other environmental conditions remains unknown. The goal of this study was to characterize the responses of GPP and SIFred to a suite of environmental drivers at the half-hour time scale and determine how these relationships change across seasons. We analyzed one year of tower-based SIFred and eddy covariance-derived GPP data from a conifer forest at Niwot Ridge, Colorado. We compared the light responses of GPP and SIFred across the year, finding that SIFred increased in response to light earlier in the year than did GPP. The light response of GPP had a positive temperature dependence in spring, and this dependency reversed in summer due to increased evaporative demand, while the light response of SIFred was less temperature dependent. Using artificial neural network ensemble analysis, we found that from spring to summer, SIFred did not exhibit a parallel response to the seasonally dynamic temperature and moisture controls on GPP. In summer SIFred was not correlated with canopy conductance, suggesting that SIF is less sensitive to stomatal control than GPP. Our results suggest that, in conifers, photosystems begin to activate in spring prior to when water becomes available for photosynthesis, presenting a challenge for the use of SIF as a phenological indicator in conifer forests.

Observing the environment in the vast inaccessible regions of Earth through remote sensing platforms provides the tools to measure ecological dynamics. The Arctic tundra biome, one of the largest i...

Warming-induced nutrient enrichment in the Arctic may lead to shifts in leaf-level physiological properties and processes with potential consequences for plant community dynamics and ecosystem function. To explore the physiological responses of Arctic tundra vegetation to increasing nutrient availability, we examined how a set of leaf nutrient and physiological characteristics of eight plant species (representing four plant functional groups) respond to a gradient of experimental nitrogen (N) and phosphorus (P) enrichment. Specifically, we examined a set of chlorophyll fluorescence measures related to photosynthetic efficiency, performance and stress, and two leaf nutrient traits (leaf %C and %N), across an experimental nutrient gradient at the Arctic Long Term Ecological Research site, located in the northern foothills of the Brooks Range, Alaska. In addition, we explicitly assessed the direct relationships between chlorophyll fluorescence and leaf %N. We found significant differences in physiological and nutrient traits between species and plant functional groups, and we found that species within one functional group (deciduous shrubs) have significantly greater leaf %N at high levels of nutrient addition. In addition, we found positive, saturating relationships between leaf %N and chlorophyll fluorescence measures across all species. Our results highlight species-specific differences in leaf nutrient traits and physiology in this ecosystem. In particular, the effects of a gradient of nutrient enrichment were most prominent in deciduous plant species, the plant functional group known to be increasing in relative abundance with warming in this ecosystem.

Three-dimensional (3D) vegetation canopy structure plays an important role in the way radiation interacts with the land surface. Accurately representing this process in Earth System models (ESMs) is crucial for the modeling of the global carbon, energy, and water cycles and hence future climate projections. Despite the importance of accounting for 3D canopy structure, the inability to represent such complexity at regional and global scales has impeded a successful implementation into ESMs. An alternative approach is to use an implicit clumping index to account for the horizontal heterogeneity in vegetation canopy representations in ESMs at global scale. This paper evaluates how modeled hyperspectral shortwave radiation partitioning of the terrestrial biosphere, as well as Sun-Induced Chlorophyll Fluorescence (SIF) are impacted when a clumping index parameterization is incorporated in the radiative transfer scheme of a new generation ESM, the Climate Model Alliance (CliMA). An accurate hyperspectral radiative transfer representation within ESMs is critical for accurately using of satellite data to confront, constrain, and improve land model processes. The newly implemented scheme is compared to Monte Carlo calculations for idealized scenes from the Radiation transfer Model Intercomparison for the Project for Intercomparison of Land-Surface Parameterizations (RAMI4PILPS), for open forest canopies both with and without snow on the ground. Results indicate that it is critical to account for canopy structural heterogeneity when calculating hyperspectral radiation transfer. The RMSE in shortwave radiation is reduced for reflectance (25%), absorptance (66%), and transmittance (75%) compared to the scenario without considering clumping. Calculated SIF is validated against satellite remote sensing data with the recently launched NASA Orbiting Carbon Observatory (OCO) 3, showing that including vertical and horizontal canopy structure when deriving SIF can improve model predictions in up to 51% in comparison to the scenario without clumping. By adding a clumping index into the CliMA-Land model, the relationship between canopy structure and SIF, Gross Primary Productivity (GPP), hyperspectral radiative transfer, and viewing geometry at the canopy scale can be explored in detail.

The connection between solar-induced fluorescence (SIF) and vegetation gross primary productivity is being widely investigated across spatial, temporal, and biological scales, including: a) studies at the leaf [1], [2], plant canopy [2]–[4] or satellite pixel scale [5], [6], b) temporally with studies spanning from diurnal [7] to seasonal scales [1], [3], [5], and b) biologically with studies covering various plant functional types (PFTs), e.g., crops [4], [7], deciduous [8] or evergreen forests [1], [3], in response to different sources of stress.

The increase in wildfire occurrence and severity seen over the past decades in the boreal and Arctic biomes is expected to continue in the future in response to rapid climate change in this region. Recent studies documented positive trends in gross primary productivity (GPP) for Arctic boreal biomes driven by warming, but it is unclear how GPP trends are affected by wildfires. Here, we used satellite vegetation observations and environmental data with a diagnostic GPP model to analyze recovery from large fires in Alaska over the period 2000–2019. We confirmed earlier findings that warmer-than-average years provide favorable climate conditions for vegetation growth, leading to a GPP increase of 1 Tg C yr−1, contributed mainly from enhanced productivity in the early growing season. However, higher temperatures increase the risk of wildfire occurrence leading to direct carbon loss over a period of 1–3 years. While mortality related to severe wildfires reduce ecosystem productivity, post-fire productivity in moderately burned areas shows a significant positive trend. The rapid GPP recovery following fires reported here might be favorable for maintaining the region's net carbon sink, but wildfires can indirectly promote the release of long-term stored carbon in the permafrost. With the projected increase in severity and frequency of wildfires in the future, we expect a reduction of GPP and therefore amplification of climate warming in this region.

Sun-induced fluorescence in the far-red region (SIF) is increasingly used as a remote and proximal-sensing tool capable of tracking vegetation gross primary production (GPP). However, the use of SIF to probe changes in GPP is challenged during extreme climatic events, such as heatwaves. Here, we examined how the 2018 European heatwave (HW) affected the GPP-SIF relationship in evergreen broadleaved trees with a relatively invariant canopy structure. To do so, we combined canopy-scale SIF measurements, GPP estimated from an eddy covariance tower, and active pulse amplitude modulation fluorescence. The HW caused an inversion of the photosynthesis-fluorescence relationship at both the canopy and leaf scales. The highly nonlinear relationship was strongly shaped by nonphotochemical quenching (NPQ), that is, a dissipation mechanism to protect from the adverse effects of high light intensity. During the extreme heat stress, plants experienced a saturation of NPQ, causing a change in the allocation of energy dissipation pathways towards SIF. Our results show the complex modulation of the NPQ-SIF-GPP relationship at an extreme level of heat stress, which is not completely represented in state-of-the-art coupled radiative transfer and photosynthesis models.

Far‐red solar‐induced chlorophyll fluorescence (SIF) has been retrieved from multiple satellites with nearly continuous global coverage since 1996. Multiple official and research‐grade retrievals provide a means for cross validation across sensors and algorithms, but produces substantial variation across products due to differences in instrument characteristics and retrieval algorithm. The lack of a consistent, calibrated SIF data set hampers scientific interpretation of planetary photosynthesis. NASA's Orbiting Carbon Observatory 2 (OCO‐2) offers small sampling footprints, high data acquisition, and repeating spatially resolved targets at bioclimatically diverse locations, providing a unique benchmark for spaceborne sensors traceable to ground data. We leverage overlap between the longer running Global Ozone Monitoring Instrument version 2 (GOME‐2) SIF time series, and more recent state‐of‐the‐art OCO‐2 and TROPOspheric Monitoring Instrument (TROPOMI) data, in a first attempt to reconcile inconsistencies in the long‐term record. After screening and correcting for key instrument differences (time of day, wavelength, Sun‐sensor geometry, cloud effects, footprint area), we find that Global Ozone Monitoring Instrument version 2 and TROPOspheric Monitoring Instrument perform exceedingly well in capturing spatial, seasonal, and interannual variability across OCO‐2 targets. However, Global Ozone Monitoring Instrument version 2 retrieval methods differ by up to a factor of 2 in signal‐to‐noise and magnitude. Magnitude differences are largely attributed to retrieval window choice, with wider windows producing higher magnitudes. The assumed SIF spectral shape has negligible effect. Substantial research is needed to understand remaining sensitivities to atmospheric absorption and reflectance. We conclude that OCO‐2 and TROPOspheric Monitoring Instrument have opened up the possibility to produce a multidecadal SIF record with well‐characterized uncertainty and error quantification for overlapping instruments, enabling back‐calibration of previous instruments and production of a consistent, research‐grade, harmonized time series.

Traditional methods of carbon monitoring in mountainous regions are challenged by complex terrain. Recently, solar‐induced fluorescence (SIF) has been found to be an indicator of gross primary production (GPP), and the increased availability of remotely sensed SIF provides an opportunity to estimate GPP across the Western United States. Although the empirical linkage between SIF and GPP is strong, the current mechanistic understanding of this linkage is incomplete and depends upon changes in leaf biochemical processes in which absorbed sunlight leads to photochemistry, heat (via nonphotochemical quenching [NPQ]), fluorescence, or tissue damage. An improved mechanistic understanding is necessary to leverage SIF observations to improve representation of ecosystem processes within land surface models. Here we included an improved fluorescence model within the Community Land Model, Version 4.5 (CLM 4.5), to simulate seasonal changes in SIF at a subalpine forest in Colorado. We found that when the model accounted for sustained NPQ, this provided a larger seasonal change in fluorescence yield leading to simulated SIF that more closely resembled the observed seasonal pattern (Global Ozone Monitoring Experiment‐2 [GOME‐2] satellite platform and a tower‐mounted spectrometer system). We found that an acclimation model based on mean air temperature was a useful predictor for sustained NPQ. Although light intensity was not an important factor for this analysis, it should be considered before applying the sustained NPQ and SIF to other cold climate evergreen biomes. More leaf‐level fluorescence measurements are necessary to better understand the seasonal relationship between sustained and reversible components of NPQ and to what extent that influences SIF.

Northern hemisphere evergreen forests assimilate a significant fraction of global atmospheric CO 2 but monitoring large-scale changes in gross primary production (GPP) in these systems is challenging. Recent advances in remote sensing allow the detection of solar-induced chlorophyll fluorescence (SIF) emission from vegetation, which has been empirically linked to GPP at large spatial scales. This is particularly important in evergreen forests, where traditional remote-sensing techniques and terrestrial biosphere models fail to reproduce the seasonality of GPP. Here, we examined the mechanistic relationship between SIF retrieved from a canopy spectrometer system and GPP at a winter-dormant conifer forest, which has little seasonal variation in canopy structure, needle chlorophyll content, and absorbed light. Both SIF and GPP track each other in a consistent, dynamic fashion in response to environmental conditions. SIF and GPP are well correlated ( R 2 = 0.62–0.92) with an invariant slope over hourly to weekly timescales. Large seasonal variations in SIF yield capture changes in photoprotective pigments and photosystem II operating efficiency associated with winter acclimation, highlighting its unique ability to precisely track the seasonality of photosynthesis. Our results underscore the potential of new satellite-based SIF products (TROPOMI, OCO-2) as proxies for the timing and magnitude of GPP in evergreen forests at an unprecedented spatiotemporal resolution.

Relatively little is known of how the world's largest vegetation transition zone – the Forest Tundra Ecotone (FTE) – is responding to climate change. Newly available, satellite-derived time-series of the photochemical reflectance index (PRI) across North America and Europe could provide new insights into the physiological response of evergreen trees to climate change by tracking changes in foliar pigment pools that have been linked to photosynthetic phenology. However, before implementing these data for such purpose at these evergreen dominated systems, it is important to increase our understanding of the fine scale mechanisms driving the connection between PRI and environmental conditions. The goal of this study is thus to gain a more mechanistic understanding of which environmental factors drive changes in PRI during late-season phenological transitions at the FTE – including factors that are susceptible to climate change (i.e., air- and soil-temperatures), and those that are not (photoperiod). We hypothesized that late-season phenological changes in foliar pigment pools captured by PRI are largely driven by photoperiod as opposed to less predictable drivers such as air temperature, complicating the utility of PRI time-series for understanding climate change effects on the FTE. Ground-based, time-series of PRI were acquired from individual trees in combination with meteorological variables and photoperiod information at six FTE sites in Alaska. A linear mixed-effects modeling approach was used to determine the significance (α = 0.001) and effect size (i.e., standardized slope b*) of environmental factors on late-seasonal changes in the PRI signal. Our results indicate that photoperiod had the strongest, significant effect on late-season changes in PRI (b* = 0.08, p

The Chlorophyll Fluorescence Imaging Spectrometer (CFIS) is an airborne high resolution imaging spectrometer built at NASA's Jet Propulsion Laboratory (JPL) for evaluating solar-induced fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2). OCO-2 is a NASA mission designed to measure atmospheric CO_2 but one of the novel data products is SIF, retrieved using reductions in the optical depth of Fraunhofer lines in OCO-2’s O_2 A-band, covering 757–775 nm at 0.042 nm spectral resolution. CFIS was specifically designed to retrieve SIF within the wavelength range of OCO-2, but extends further down to 737 nm, nearly maintaining the high spectral resolution of the OCO-2 instrument (0.07 vs. 0.042 nm). Here, we provide an overview of the instrument calibration and performance as well as the retrieval strategy based on non-linear weighted least-squares. To illustrate the retrieval performance using actual flight data, we focus on data acquired over agricultural fields in Mead, Nebraska from an unpressurized Twin Otter (DHC-6) aircraft at a flight altitude of 3000 m above ground level (AGL). Spectral residuals are consistent with expected detector noise, which enables us to compute realistic 1-σ precision errors of 0.5–0.7 W/m^2/sr/μm for typical SIF retrievals, which can be reduced to

Chlorophyll fluorescence (ChlF) takes place in green leaves of the plants during photosynthesis. It has therefore been proposed that ChlF can be used to track the photosynthetic activity of plants and the current possibility to observe sun-induced chlorophyll fluorescence (SIF) via remote sensing provides an unprecedented tool to monitor terrestrial photosynthesis at global scale. However, the relationship between photosynthesis and ChlF is not linear at all scales and is partly controlled by the non-photochemical quenching - which dissipates excess energy as heat. The relationship between the photochemical and fluorescence yields changes when the photochemical quenching is dominating at low irradiance conditions or at high stress conditions. Interpretation of observed SIF is complicated by its dependence on incoming absorbed radiation, observation geometry and radiative transfer of SIF photons within the canopy. To fully exploit remotely sensed SIF to estimate photosynthesis at ecosystem and global scales, it is important to account for these aspects through modelling that include ecosystem processes.In this work we have implemented a ChlF model into a state-of-the-art land surface model QUantifying Interactions between terrestrial Nutrient CYcles and the climate system (QUINCY) simulating the terrestrial energy, water and biogeochemical cycles of carbon, nitrogen and phosphorus. The simulation of radiative transfer is highly influential for the simulated SIF signal, but the complex solutions of radiative transfer are computationally too heavy, making them impractical approaches at global scale. Therefore, we have investigated different radiative transfer techniques for the SIF signal of varying complexity at site scale in Niwot Ridge, U.S. The most complex solution is based on the mSCOPE and Fluspects model, that explicitly calculates signal transfer. The intermediate solution is based on a two-stream flux approach and the most simple is using a simple fraction for the escape ratio of SIF. Our aim is to assess which solution is most suitable for simulating the SIF signal at different scales and also test different formulations for modelling of non-photochemical quenching.

Solar-Induced chlorophyll Fluorescence (SIF) provides a powerful proxy for determining forest gross primary production (GPP), particularly in evergreen ecosystems where traditional measures of gree...

Solar-induced fluorescence (SIF) is a promising tool to estimate photosynthesis across scales; however, there has been limited research done at the leaf level to investigate the relationship between SIF and photosynthesis. To help bridge this gap, a LI-COR LI-6800 gas exchange instrument was modified with a visible-near-infrared (VIS-NIR) spectrometer to measure active and passive fluorescence simultaneously. The system was adapted by drilling a hole into the bottom plate of the leaf chamber and inserting a fibre-optic to measure passive steady-state fluorescence (Ft,λ, analogous to SIF) from the abaxial surface of a leaf. This new modification can concurrently measure gas exchange, passive fluorescence and active fluorescence over the same leaf area and will allow researchers to measure leaf-level Ft,λ in the field to validate tower-based and satellite measurements. To test the modified instrument, measurements were performed on leaves of well-watered and water-stressed walnut plants at three light levels and a constant air temperature. Measurements on these same plants were also conducted using a similarly modified Walz GFS-3000 gas exchange instrument to compare results. We found a positive linear correlation between Ft,λ measurements from the modified LI-6800 and GFS-3000 instruments. We also report a positive linear relationship between Ft,λ and normalized steady-state chlorophyll fluorescence (Ft/Fo) from the pulse-amplitude modulation (PAM) fluorometer of the LI-6800 system. Accordingly, this modification will inform the link between spectrally resolved Ft,λ and gas exchange—leading to improved interpretation of how remotely sensed SIF tracks changes in the light reactions of photosynthesis.

At the seasonal timescale, daily photochemical reflectance index (PRI) measurements track changes in photoprotective pigment pools as plants respond to seasonally variable environmental conditions. As such, remotely‐sensed PRI products present opportunities to study seasonal processes in evergreen conifer forests, where complex vegetation dynamics are difficult to capture due to small annual changes in chlorophyll content or leaf structure. Because PRI is tied explicitly to short and long term changes in photoprotective pigments that are responsible for regulating stress, we hypothesize that PRI by extension could serve as a proxy for stomatal response to seasonally changing hydroclimate, assuming plant functional responses to stress covary in space and time. To test this, we characterized PRI in a semi‐arid, montane mixed conifer forest in the Madrean sky islands of Arizona, USA during the monsoon growing season subject to precipitation pulse dynamics. To determine the sensitivity of PRI to ecohydrologic variability and associated changes in gross primary productivity (GPP), canopy spectral measurements were coupled with eddy covariance CO₂ flux and sap flow measurements. Seasonally, there was a significant relationship between PRI and sap flow velocity (R²=0.56), and multiple linear regression analysis demonstrated a PRI response to dynamic water and energy limitations in this system. We conclude that PRI has potential to serve as a proxy for forest functional response to seasonal ecohydrologic forcing. The coordination between photoprotective pigments and seasonal stomatal regulation demonstrated here could aid characterization of vegetation response to future changes in hydroclimate at increasing spatial scales.

Chlorophyll fluorescence (ChIF) is emitted in the range of 640–850 nm, with two local maxima (peaks) - at around 685 and 740 nm, respectively. The spectral shape and peak positions of the ChlF spectrum carries information of plant photosynthetic status. A preliminary study based on experimental data about the ChlF peak positions under different conditions, such as species, chlorophyll content, photosynthetically active radiation, irrigation conditions, are presented. The results show that herbaceous and woody plants have different distributions of the ChlF peak positions. The far-red peak positions shift to longer wavelength when chlorophyll content increases, while the red peak positions do not show a clear changing pattern. Besides, incident PAR levels also have a noticeable effect on the shift of the ChlF peak positions. Finally, the far-red peak positions span a broader distribution under drought-stress condition.

The understanding and modeling of photosynthetic dynamics affected by climate variability can be highly uncertain. In this paper, we examined a well‐characterized eddy covariance site in a drought‐prone temperate deciduous broadleaf forest combining tower measurements and satellite observations. We find that an increase in spring temperature usually leads to enhanced spring gross primary production (GPP), but a GPP reduction in late growing season due to water limitation. We evaluated how well a coupled fluorescence‐photosynthesis model (SCOPE) and satellite data sets track the interannual and seasonal variations of tower GPP from 2007 to 2016. In SCOPE, a simple stress factor scaling of Vcmax as a linear function of observed predawn leaf water potential (ψ_(pd)) shows a good agreement between modeled and measured interannual variations in both GPP and solar‐induced chlorophyll fluorescence (SIF) from the Global Ozone Monitoring Experiment‐2 (GOME‐2). The modeled and satellite‐observed changes in SIF_(yield) are ~30% smaller than corresponding changes in light use efficiency (LUE) under severe stress, for which a common linear SIF to GPP scaling would underestimate the stress reduction in GPP. Overall, GOME‐2 SIF tracks interannual tower GPP variations better than satellite vegetations indices (VIs) representing canopy “greenness.” However, it is still challenging to attribute observed SIF variations unequivocally to greenness or physiological changes due to large GOME‐2 footprint. Higher‐resolution SIF data sets (e.g., TROPOMI) already show the potential to well capture the downregulation of late‐season GPP and could pave the way to better disentangle canopy structural and physiological changes in the future.

Observations of solar‐induced chlorophyll a fluorescence (SIF) from spaceborne spectrometers can advance our understanding of terrestrial and aquatic carbon cycles. Here we present the first global retrievals of SIF at red wavelengths from the TROPOspheric Monitoring Instrument (TROPOMI). Despite the weak signal level, considerable uncertainties, and subtle measurement artifacts, spatial patterns and magnitudes agree with independent data sets. Over land, spatial patterns of our red SIF estimates covary with the far‐red SIF data. Red SIF over the ocean is highly consistent with the normalized fluorescence line height (nFLH) inferred from measurements of the MODerate resolution Imaging Spectroradiometer (MODIS), even when comparing single days and fine spatial scales. Major advantages of our Fraunhofer line‐based SIF retrievals include the capability to sense SIF through optically thin cloud/aerosol layers and an insensitivity to ocean color. This opens up new avenues for studying ocean biogeochemistry from space.

Remote sensing of solar‐induced chlorophyll fluorescence (SIF) offers potential to infer photosynthesis across scales and biomes. Many retrieval methods have been developed to estimate top‐of‐canopy SIF using ground‐based spectroscopy. However, inconsistencies among methods may confound interpretation of SIF dynamics, eco‐physiological/environmental drivers, and its relationship with photosynthesis. Using high temporal‐ and spectral resolution ground‐based spectroscopy, we aimed to (1) evaluate performance of SIF retrieval methods under diverse sky conditions using continuous field measurements; (2) assess method sensitivity to fluctuating light, reflectance, and fluorescence emission spectra; and (3) inform users for optimal ground‐based SIF retrieval. Analysis included field measurements from bi‐hemispherical and hemispherical‐conical systems and synthetic upwelling radiance constructed from measured downwelling radiance, simulated reflectance, and simulated fluorescence for benchmarking. Fraunhofer‐based differential optical absorption spectroscopy (DOAS) and singular vector decomposition (SVD) retrievals exhibit convergent SIF‐PAR relationships and diurnal consistency across different sky conditions, while O₂A‐based spectral fitting method (SFM), SVD, and modified Fraunhofer line discrimination (3FLD) exhibit divergent SIF‐PAR relationships across sky conditions. Such behavior holds across system configurations, though hemispherical‐conical systems diverge less across sky conditions. O₂A retrieval accuracy, influenced by atmospheric distortion, improves with a narrower fitting window and when training SVD with temporally local spectra. This may impact SIF‐photosynthesis relationships interpreted by previous studies using O₂A‐based retrievals with standard (759–767.76 nm) fitting windows. Fraunhofer‐based retrievals resist atmospheric impacts but are noisier and more sensitive to assumed SIF spectral shape than O₂A‐based retrievals. We recommend SVD or SFM using reduced fitting window (759.5–761.5 nm) for robust far‐red SIF retrievals across sky conditions.

Recent advancements in understanding remotely sensed solar‐induced chlorophyll fluorescence often suggest a linear relationship with gross primary productivity at large spatial scales. However, the quantum yields of fluorescence and photochemistry are not linearly related, and this relationship is largely driven by irradiance. This raises questions about the mechanistic basis of observed linearity from complex canopies that experience heterogeneous irradiance regimes at subcanopy scales. We present empirical data from two evergreen forest sites that demonstrate a nonlinear relationship between needle‐scale observations of steady‐state fluorescence yield and photochemical yield under ambient irradiance. We show that accounting for subcanopy and diurnal patterns of irradiance can help identify the physiological constraints on needle‐scale fluorescence at 70–80% accuracy. Our findings are placed in the context of how solar‐induced chlorophyll fluorescence observations from spaceborne sensors relate to diurnal variation in canopy‐scale physiology.

Timely and accurate monitoring of crops is essential for food security. Here, we examine how well solar-induced chlorophyll fluorescence (SIF) can inform crop productivity across the United States. Based on tower-level observations and process-based modeling, we find highly linear gross primary production (GPP):SIF relationships for C4 crops, while C3 crops show some saturation of GPP at high light when SIF continues to increase. C4 crops yield higher GPP:SIF ratios (30�50) primarily because SIF is most sensitive to the light reactions (does not account for photorespiration). Scaling to the satellite, we compare SIF from the TROPOspheric Monitoring Instrument (TROPOMI) against tower-derived GPP and county-level crop statistics. Temporally, TROPOMI SIF strongly agrees with GPP observations upscaled across a corn and soybean dominated cropland (R2 = 0.89). Spatially, county-level TROPOMI SIF correlates with crop productivity (R2 = 0.72; 0.86 when accounting for planted area and C3/C4 contributions), highlighting the potential of SIF for reliable crop monitoring. ©2020. American Geophysical Union. All Rights Reserved.

While large-scale floods directly impact human lives and infrastructures, they also profoundly impact agricultural productivity. New satellite observations of vegetation activity and atmospheric CO2 offer the opportunity to quantify the effects of such extreme events on cropland carbon sequestration, which are important for mitigation strategies. Widespread flooding during spring and early summer 2019 delayed crop planting across the U.S. Midwest. As a result, satellite observations of solar-induced chlorophyll fluorescence (SIF) from TROPOspheric Monitoring Instrument (TROPOMI) and Orbiting Carbon Observatory (OCO-2) reveal a shift of 16 days in the seasonal cycle of photosynthetic activity relative to 2018, along with a 15% lower peak photosynthesis. We estimate the 2019 anomaly to have led to a reduction of -0.21 PgC in gross primary production (GPP) in June and July, partially compensated in August and September (+0.14 PgC). The extension of the 2019 growing season into late September is likely to have benefited from increased water availability and late-season temperature. Ultimately, this change is predicted to reduce the crop yield over most of the midwest Corn/Soy belt by ~15%. Using an atmospheric transport model, we show that a decline of ~0.1 PgC in the net carbon uptake during June and July is consistent with observed CO2 enhancements from Atmospheric Carbon and Transport - America (ACT-America) aircraft and OCO-2. This study quantifies the impact of floods on cropland productivity and demonstrates the potential of combining SIF with atmospheric CO2 observations to monitor regional carbon flux anomalies.

While large‐scale floods directly impact human lives and infrastructures, they also profoundly impact agricultural productivity. New satellite observations of vegetation activity and atmospheric CO₂ offer the opportunity to quantify the effects of such extreme events on cropland carbon sequestration. Widespread flooding during spring and early summer 2019 induced conditions that delayed crop planting across the U.S. Midwest. As a result, satellite observations of solar‐induced chlorophyll fluorescence from TROPOspheric Monitoring Instrument and Orbiting Carbon Observatory reveal a 16‐day shift in the seasonal cycle of photosynthesis relative to 2018, along with a 15% lower peak value. We estimate a reduction of 0.21 PgC in cropland gross primary productivity in June and July, partially compensated in August and September (+0.14 PgC). The extension of the 2019 growing season into late September is likely to have benefited from increased water availability and late‐season temperature. Ultimately, this change is predicted to reduce the crop productivity in the Midwest Corn/Soy belt by ~15% compared to 2018. Using an atmospheric transport model, we show that a decline of ~0.1 PgC in the net carbon uptake during June and July is consistent with observed CO₂ enhancements of up to 10 ppm in the midday boundary layer from Atmospheric Carbon and Transport‐America aircraft and over 3 ppm in column‐averaged dry‐air mole fractions from Orbiting Carbon Observatory. This study quantifies the impact of floods on cropland productivity and demonstrates the potential of combining solar‐induced chlorophyll fluorescence with atmospheric CO₂ observations to monitor regional carbon flux anomalies.

Recent successes in passive remote sensing of far-red solar induced chlorophyll fluorescence (SIF) have spurred development and integration of canopy-level fluorescence models in global terrestrial biosphere models (TBMs) for climate and carbon cycle research. The interaction of fluorescence with photochemistry at the leaf- and canopy- scale provides opportunities to diagnose and constrain model simulations of photosynthesis and related processes, through direct comparison to and assimilation of tower, airborne, and satellite data. TBMs describe key processes relating to absorption of sunlight, leaf-level fluorescence emission, scattering and reabsorption throughout the canopy. Here, we analyze simulations from an ensemble of process-based TBM-SIF models (SiB3, SiB4, CLM4.5, CLM5.0, BETHY, ORCHIDEE, BEPS) at a subalpine evergreen needleleaf forest near Niwot Ridge, Colorado. These models are forced with tower observed meteorological data, and analyzed against continuous far-red SIF and gross primary productivity (GPP) partitioned eddy covariance data at diurnal and synoptic scales during the growing season (July–August 2017). Our primary objective is to summarize the site-level state of the art in TBM-SIF modeling over a relatively short time period (summer) when light, structure, and pigments are similar, setting the stage for regional- to global-scale analyses. We find that these models are generally well constrained in simulating photosynthetic yield, but show strongly divergent patterns in the simulation of absorbed photosynthetic active radiation (PAR), absolute GPP and fluorescence, quantum yields, and light response at leaf and canopy scale. This study highlights the need for mechanistic modeling of non-photochemical quenching in stressed and unstressed environments, and improved representation of light absorption (APAR), distribution of sunlit and shaded light, and radiative transfer from leaf to canopy scale.

Solar-induced chlorophyll fluorescence (SIF) has been shown to be a powerful proxy for photosynthesis and gross primary productivity (GPP). The recently launched TROPOspheric Monitoring Instrument (TROPOMI) features the required spectral resolution and signal-to-noise ratio to retrieve SIF from space. Here, we present a downscaling method to obtain 500 m spatial resolution SIF over California. We report daily values based on a 14 d window. TROPOMI SIF data show a strong correspondence with daily GPP estimates at AmeriFlux sites across multiple ecosystems in California. We find a linear relationship between SIF and GPP that is largely invariant across ecosystems with an intercept that is not significantly different from zero. Measurements of SIF from TROPOMI agree with MODerate Resolution Imaging Spectroradiometer (MODIS) vegetation indices – the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near-infrared reflectance of vegetation index (NIR_v) – at annual timescales but indicate different temporal dynamics at monthly and daily timescales. TROPOMI SIF data show a double peak in the seasonality of photosynthesis, a feature that is not present in the MODIS vegetation indices. The different seasonality in the vegetation indices may be due to a clear-sky bias in the vegetation indices, whereas previous work has shown SIF to have a low sensitivity to clouds and to detect the downregulation of photosynthesis even when plants appear green. We further decompose the spatiotemporal patterns in the SIF data based on land cover. The double peak in the seasonality of California's photosynthesis is due to two processes that are out of phase: grasses, chaparral, and oak savanna ecosystems show an April maximum, while evergreen forests peak in June. An empirical orthogonal function (EOF) analysis corroborates the phase offset and spatial patterns driving the double peak. The EOF analysis further indicates that two spatiotemporal patterns explain 84 % of the variability in the SIF data. Results shown here are promising for obtaining global GPP at sub-kilometer spatial scales and identifying the processes driving carbon uptake.

Carbon uptake and tree growth are important factors for assessing productivity and long-term carbon storage. Measurements of radial stem growth are mainly performed at the individual tree scale and can be used to infer ecosystem net primary productivity (NPP). However, these measurements are spatially limited, and remote sensing provides a promising tool to track vegetation function and productivity across spatial scales, making it a viable technique for assessing variation in interannual tree growth and carbon storage. In this study we examined the correspondence between in-situ annual tree-ring width across four dominant evergreen species in the Sierra Nevada and a wide range of remotely sensed products linked to carbon uptake including NPP, gross primary productivity (GPP), net photosynthesis (PSN), normalized difference vegetation index (NDVI), near infrared reflectance of vegetation index (NIRV), and chlorophyll/carotenoid index (CCI) from MODIS (Moderate resolution Imaging Spectroradiometer) as well as downscaled solar-induced fluorescence (SIF) products, using a 14 year dataset (2000–2014) across 62 forest sites. We show that variation of annual tree-ring width was best captured by the annual sum of MODIS GPP, with a legacy effect (5-month backwards shift). Across all forest sites, MODIS GPP with a 5-month legacy effect showed moderate correspondence with tree-ring width (r = 0.60). Within each individual site, however, the interannual correspondence between MODIS GPP with a legacy effect and tree growth was stronger (median r = 0.70 vs 0.14 without a legacy effect). The importance of legacy effects in explaining tree growth variation within sites indicates that tree growth each year is influenced by carbon uptake during the latter part of the previous growing season. Additional local environmental factors also explained annual variation in tree-ring width, including (in descending order of importance) local tree density, latitude, slope, DBH, elevation and aspect.

The Arctic-Boreal Zone (ABZ) is characterized by spatially heterogeneous vegetation composition and structure, leading to challenges for inferring patterns in vegetation productivity. A mechanistic understanding of the patterns and processes underlying spectral remote sensing observations is necessary to overcome these challenges. Solar-induced chlorophyll fluorescence (SIF), near-infrared reflectance of vegetation (NIRv), and chlorophyll/carotenoid index (CCI) show promise for tracking productivity and disentangling links to the activity and distribution of chlorophyll at coarse spatial scales (e.g. 0.5°), but their effectiveness for studying mixed landscapes characteristic of the ABZ remains unclear. Here, we use airborne observations collected during NASA’s Arctic-Boreal Vulnerability Experiment to examine the spatial covariation between SIF, NIRv, and CCI at a scale (30 m) commensurate with the best available landcover products across interior Alaska. Additionally, we compare relationships among SIF and vegetation indices from spaceborne observations (TROPOMI and MODIS) resampled to a 0.01° (∼1000 m) scale. We find that the strength of the SIF-NIRv linear relationship degrades when compared from the spaceborne to the airborne scale (R 2 = 0.50 vs. 0.26) as does the strength of the SIF-CCI linear relationship (R 2 = 0.30 vs. 0.18), though the degradation of SIF-CCI is less severe than that of SIF-NIRv. The relationship of SIF with either vegetation index is strongly dependent on landcover class at both airborne and spaceborne scales. We provide context for how further work could leverage SIF with reflectance indices measurable from a variety of platforms to improve mapping of vegetation dynamics in this ecoregion.

When the capacity for photosynthesis is constrained by unfavorable growing conditions, excess absorbed light is safely lost from leaves via thermal energy dissipation—a photoprotective mechanism ubiquitous among higher plants. The relatively low irradiance conditions yet stressful growing environment of the arctic tundra suggest contrasting hypotheses regarding the necessity for plant investment in photoprotection. To examine these hypotheses, the photoprotective pigments of the xanthophyll cycle were investigated in conjunction with non-photochemical quenching (NPQ) of chlorophyll fluorescence emission in two dominant arctic shrub species, Salix pulchra and Betula nana. The xanthophyll cycle pool sizes of S. pulchra leaves were substantially higher than those reported in most other higher plant species, whereas B. nana leaves maintain modestly high xanthophyll cycle pool sizes. In addition, high retention of de-epoxidized xanthophyll cycle pigments in both species and saturation of xanthophyll c...